Zobrazeno 1 - 10
of 55
pro vyhledávání: '"Paul, Maria P."'
Autor:
Scheikl, Paul Maria, Tagliabue, Eleonora, Gyenes, Balázs, Wagner, Martin, Dall'Alba, Diego, Fiorini, Paolo, Mathis-Ullrich, Franziska
Publikováno v:
IEEE Robotics and Automation Letters 8 (2023) 560-567
Automation holds the potential to assist surgeons in robotic interventions, shifting their mental work load from visuomotor control to high level decision making. Reinforcement learning has shown promising results in learning complex visuomotor polic
Externí odkaz:
http://arxiv.org/abs/2406.06092
Autor:
Scheikl, Paul Maria, Schreiber, Nicolas, Haas, Christoph, Freymuth, Niklas, Neumann, Gerhard, Lioutikov, Rudolf, Mathis-Ullrich, Franziska
Publikováno v:
IEEE Robotics and Automation Letters 9 (2024) 5338-5345
Policy learning in robot-assisted surgery (RAS) lacks data efficient and versatile methods that exhibit the desired motion quality for delicate surgical interventions. To this end, we introduce Movement Primitive Diffusion (MPD), a novel method for i
Externí odkaz:
http://arxiv.org/abs/2312.10008
Autor:
Henrich, Pit, Gyenes, Balázs, Scheikl, Paul Maria, Neumann, Gerhard, Mathis-Ullrich, Franziska
In deformable object manipulation, we often want to interact with specific segments of an object that are only defined in non-deformed models of the object. We thus require a system that can recognize and locate these segments in sensor data of defor
Externí odkaz:
http://arxiv.org/abs/2311.07357
Autor:
Josiah Roberts, Biswas Rijal, Simon Divilov, Jon-Paul Maria, William G. Fahrenholtz, Douglas E. Wolfe, Donald W. Brenner, Stefano Curtarolo, Eva Zurek
Publikováno v:
npj Computational Materials, Vol 10, Iss 1, Pp 1-10 (2024)
Abstract Large-density functional theory (DFT) databases are a treasure trove of energies, forces, and stresses that can be used to train machine-learned interatomic potentials for atomistic modeling. Herein, we employ structural relaxations from the
Externí odkaz:
https://doaj.org/article/bc840544e1124a0abfc44bf9989d0d56
Autor:
Linkerhägner, Jonas, Freymuth, Niklas, Scheikl, Paul Maria, Mathis-Ullrich, Franziska, Neumann, Gerhard
Physical simulations that accurately model reality are crucial for many engineering disciplines such as mechanical engineering and robotic motion planning. In recent years, learned Graph Network Simulators produced accurate mesh-based simulations whi
Externí odkaz:
http://arxiv.org/abs/2302.11864
LapGym -- An Open Source Framework for Reinforcement Learning in Robot-Assisted Laparoscopic Surgery
Autor:
Scheikl, Paul Maria, Gyenes, Balázs, Younis, Rayan, Haas, Christoph, Neumann, Gerhard, Wagner, Martin, Mathis-Ullrich, Franziska
Recent advances in reinforcement learning (RL) have increased the promise of introducing cognitive assistance and automation to robot-assisted laparoscopic surgery (RALS). However, progress in algorithms and methods depends on the availability of sta
Externí odkaz:
http://arxiv.org/abs/2302.09606
Autor:
Mingze He, Joseph R. Matson, Mingyu Yu, Angela Cleri, Sai S. Sunku, Eli Janzen, Stefan Mastel, Thomas G. Folland, James H. Edgar, D. N. Basov, Jon-Paul Maria, Stephanie Law, Joshua D. Caldwell
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-8 (2023)
Abstract Hyperbolic phonon polaritons (HPhPs) can be supported in materials where the real parts of their permittivities along different directions are opposite in sign. HPhPs offer confinements of long-wavelength light to deeply subdiffractional sca
Externí odkaz:
https://doaj.org/article/49caab8dfe6542eb920d3b8f72bf3934
Autor:
Scheikl, Paul Maria, Gyenes, Balázs, Davitashvili, Tornike, Younis, Rayan, Schulze, André, Müller-Stich, Beat P., Neumann, Gerhard, Wagner, Martin, Mathis-Ullrich, Franziska
Cognitive cooperative assistance in robot-assisted surgery holds the potential to increase quality of care in minimally invasive interventions. Automation of surgical tasks promises to reduce the mental exertion and fatigue of surgeons. In this work,
Externí odkaz:
http://arxiv.org/abs/2110.04857
Publikováno v:
APL Materials, Vol 12, Iss 2, Pp 021105-021105-7 (2024)
The discovery of ferroelectricity in polar wurtzite-based ternary materials, such as Al1−xBxN, has attracted attention due to their compatibility with complementary metal–oxide–semiconductor processes and potential use in integrated non-volatil
Externí odkaz:
https://doaj.org/article/bb0b0a997ce64e2eb42a85b29cc69bda
Autor:
Yongtao Liu, Anton Ievlev, Joseph Casamento, John Hayden, Susan Trolier‐McKinstry, Jon‐Paul Maria, Sergei V. Kalinin, Kyle P. Kelley
Publikováno v:
Advanced Electronic Materials, Vol 10, Iss 2, Pp n/a-n/a (2024)
Abstract Polarization dynamics and domain structure evolution in ferroelectric Al0.93B0.07N are studied using piezoresponse force microscopy and spectroscopies in ambient and controlled atmosphere environments. The application of negative unipolar an
Externí odkaz:
https://doaj.org/article/c547e5e5bdf84942b5ff0f348fcb6ea2